TY - JOUR

T1 - Structural equation modeling in management research

T2 - a guide for improved analysis

AU - Williams, Larry J.

AU - Vandenberg, Robert J.

AU - Edwards, Jeffrey R.

PY - 2009

Y1 - 2009

N2 - A large segment of management research in recent years has used structural equation modeling (SEM) as an analytical approach that simultaneously combines factor analysis and linear regression models for theory testing. With this approach, latent variables (factors) represent the concepts of a theory, and data from measures (indicators) are used as input for statistical analyses that provide evidence about the relationships among latent variables. This chapter first provides a brief introduction to SEM and its concepts and terminology. We then discuss four issues related to the measurement component of such models, including how indicators are developed, types of relationships between indicators and latent variables, approaches for multidimensional constructs, and analyses needed when data from multiple time points or multiple groups are examined. In our second major section, we focus on six issues related to the structural component of structural equation models, including how to examine mediation and moderation, dealing with longitudinal and multilevel data, issues related to the use of control variables, and judging the adequacy of models and latent variable relationships. We conclude with a set of recommendations for how future applications of SEM in management research can be improved.

AB - A large segment of management research in recent years has used structural equation modeling (SEM) as an analytical approach that simultaneously combines factor analysis and linear regression models for theory testing. With this approach, latent variables (factors) represent the concepts of a theory, and data from measures (indicators) are used as input for statistical analyses that provide evidence about the relationships among latent variables. This chapter first provides a brief introduction to SEM and its concepts and terminology. We then discuss four issues related to the measurement component of such models, including how indicators are developed, types of relationships between indicators and latent variables, approaches for multidimensional constructs, and analyses needed when data from multiple time points or multiple groups are examined. In our second major section, we focus on six issues related to the structural component of structural equation models, including how to examine mediation and moderation, dealing with longitudinal and multilevel data, issues related to the use of control variables, and judging the adequacy of models and latent variable relationships. We conclude with a set of recommendations for how future applications of SEM in management research can be improved.

U2 - 10.1080/19416520903065683

DO - 10.1080/19416520903065683

M3 - Journal article

VL - 3

SP - 543

EP - 604

JO - The Academy of Management Annals

JF - The Academy of Management Annals

SN - 1941-6520

IS - 1

ER -